Project Summary Efficient cognitive processing relies on the brain?s ability to engage in prediction and to use forward modeling to anticipate cognitive events, including during language processing. The central goal of this proposal is to test two competing hypotheses concerning how age influences prediction during auditory and visual language processing. Current evidence is contradictory and sparse, reflecting the need for systematic investigation. The project has three Specific Aims: Aim1: Determine whether older adults predict words in manipulated sentence contexts less or more than younger adults do by examining prediction during reading, using both electrophysiology (EEG) and eyetracking methods. Aim2: Determine whether, during spoken language processing, older adults predict words in manipulated sentence contexts less or more than younger adults do, using EEG and Visual World eyetracking methods. Spoken language processing merits targeted investigation because evidence suggests older adults have specific problems with auditory input. Moreover, in the young adult literature on prediction in language processing, relatively few studies have focused on spoken language, so little is known about whether prediction differs in the two modalities. Aim3: Determine whether older adults predict upcoming words in connected passages less or more than younger adults do, using fixation-related fMRI and EEG methods in reading, with prediction assessed by continuous measures of lexical surprisal and entropy. Surprisal and entropy measures permit the investigation of more naturally varying levels of predictability, more natural distributions of predictable and less predictable information, and allow the investigation of how natural texts (i.e., stimuli not specifically created for an experiment) are comprehended. Innovations: The project is innovative in (1) the use of converging eyetracking, EEG, and fMRI methods to systematically evaluate the extent of prediction during older adults' language comprehension, emphasizing replication across techniques and modalities; (2) the use of continuously varying surprisal/entropy in connected text to index age differences in prediction; (3) the use of a novel technique developed by PI Henderson, Fixation-Related fMRI, to relate neural activation to word-by-word surprisal and entropy during natural reading. Significance: The experiments will yield high temporal resolution information about prediction in older adults during online reading and spoken comprehension, together with detailed information about the neural bases of prediction operations. The findings have important implications for theories of normal cognitive aging. Translational significance: A psychometrically valid assessment of everyday language skills will be used to evaluate the relationship between prediction skills and a measure that has been shown to predict impairments associated with Alzheimer?s disease. Overall, prediction in language processing is potentially a model system for enhancing our scientific understanding of how cognitive and neural decline associated with aging trades off against greater knowledge and experience.